Repeated administration of central stimulants (e.g., methamphetamine (MA); cocaine) sensitizes neural circuits that assign biological significance to drugs and drug-related cues, leading to increased drug-directed motivation and craving during periods of remission. Locomotor sensitization provides a behavioral record of these neural changes. However, there is genotype-dependent variation in the magnitude of sensitization that is induced by repeated, intermittent stimulant treatment. Furthermore, although the molecular mechanisms related to robust sensitization have been determined in some detail (e.g., Robison & Nestler, 2011), the specific genetic relationships between magnitude of sensitization and amount of voluntary drug intake are not known. The goal of the current research is to extend knowledge beyond awareness that the nucleus accumbens shell is a critical neural substrate of changes induced by repeated MA treatment, to identification of neural nodes and associated molecular mechanisms for both sensitization and MA intake. Transcriptome analysis will also be performed in the central nucleus of the amygdala, known to be critical for MA craving (e.g., Li et al., 2015), to determine regulatory events relevant to risk for MA sensitization and consumption. This application has 4 specific aims. In the first aim, 2 replicate sets of short-term selected lins will be created from heterogeneous stock-collaborative cross (HS-CC) founders that are methamphetamine (MA) sensitization prone (MASP) and resistant (MASR). Two sets will be created so that data can be carefully screened for replicability. These lines will be tested for MA intake. In the second aim, two replicate sets of short-term selected lines will be created from the HS-CC that is high (MAH) and low (MAL) MA consumers. These lines will also be tested for MA-induced sensitization. The third aim will use RNA-Seq and Weighted Gene Co- expression Network Analysis (WGCNA) to examine how selection affects gene transcriptional connectivity in the nucleus accumbens and central nucleus of the amygdala for each selection trait. The consensus network approach to be used will allow us to determine which co expression modules are most closely linked to functional change associated with risk (i.e., differences between the selected lines in a drug-free state). In addition, genotype data from RNA-Seq will be used to perform quantitative trait locus (QTL) analysis and identify the locations of trait-relevant genes. Finally, the fourth aim will be to manipulate key hub genes using RNA interference vectors and then examine the effect on the selected trait. This will directly test our transcriptional connectivity findings. Accomplishing this set of aims would provide critical molecular level data pertaining to the relationship between genetic risk for MA-induced neuroplasticity and intake. Use of the HS- CC is particularly important because this mouse stock captures ~90% of the genetic diversity in Mus musculus and better represents the kind of genetic diversity found in human populations.